The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries
This paper introduces the Electric Vehicle Routing Problem with Drones (EVRPD), the first VRP combining electric ground vehicles (EVs) with unmanned aerial vehicles (UAVs), also known as drones, in order to deliver packages to customers. The problem’s objective is to minimize the total energy consum...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | Cleaner Logistics and Supply Chain |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772390922000142 |
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| author | Nikolaos A. Kyriakakis Themistoklis Stamadianos Magdalene Marinaki Yannis Marinakis |
| author_facet | Nikolaos A. Kyriakakis Themistoklis Stamadianos Magdalene Marinaki Yannis Marinakis |
| author_sort | Nikolaos A. Kyriakakis |
| collection | DOAJ |
| description | This paper introduces the Electric Vehicle Routing Problem with Drones (EVRPD), the first VRP combining electric ground vehicles (EVs) with unmanned aerial vehicles (UAVs), also known as drones, in order to deliver packages to customers. The problem’s objective is to minimize the total energy consumption, focusing on the main non-constant and controllable factor of energy consumption on a delivery vehicle, the payload weight. The problem considers same-sized packages, belonging to different weight classes. EVs serve as motherships, from which drones are deployed to deliver the packages. Drones can carry multiple packages, up to a certain weight limit and their range is depended on their payload weight. For solving the EVRPD, four algorithms of the Ant Colony Optimization framework are implemented, two versions of the Ant Colony System and the Min–Max Ant System. A Variable Neighborhood Descent algorithm is utilized in all variants as a local search procedure. Instances for the EVRPD are created based on the two-echelon VRP literature and are used to test the proposed algorithms. Their computational results are compared and discussed. Practical, real-life scenarios of the EVRPD application are also presented and solved. |
| format | Article |
| id | doaj-art-c2e37a059a804992bd51ed98a686cce3 |
| institution | Kabale University |
| issn | 2772-3909 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cleaner Logistics and Supply Chain |
| spelling | doaj-art-c2e37a059a804992bd51ed98a686cce32024-11-23T06:31:49ZengElsevierCleaner Logistics and Supply Chain2772-39092022-07-014100041The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveriesNikolaos A. Kyriakakis0Themistoklis Stamadianos1Magdalene Marinaki2Yannis Marinakis3Technical University of Crete, School of Production Engineering and Management, University Campus, 73100 Chania, GreeceTechnical University of Crete, School of Production Engineering and Management, University Campus, 73100 Chania, GreeceTechnical University of Crete, School of Production Engineering and Management, University Campus, 73100 Chania, GreeceCorresponding author.; Technical University of Crete, School of Production Engineering and Management, University Campus, 73100 Chania, GreeceThis paper introduces the Electric Vehicle Routing Problem with Drones (EVRPD), the first VRP combining electric ground vehicles (EVs) with unmanned aerial vehicles (UAVs), also known as drones, in order to deliver packages to customers. The problem’s objective is to minimize the total energy consumption, focusing on the main non-constant and controllable factor of energy consumption on a delivery vehicle, the payload weight. The problem considers same-sized packages, belonging to different weight classes. EVs serve as motherships, from which drones are deployed to deliver the packages. Drones can carry multiple packages, up to a certain weight limit and their range is depended on their payload weight. For solving the EVRPD, four algorithms of the Ant Colony Optimization framework are implemented, two versions of the Ant Colony System and the Min–Max Ant System. A Variable Neighborhood Descent algorithm is utilized in all variants as a local search procedure. Instances for the EVRPD are created based on the two-echelon VRP literature and are used to test the proposed algorithms. Their computational results are compared and discussed. Practical, real-life scenarios of the EVRPD application are also presented and solved.http://www.sciencedirect.com/science/article/pii/S2772390922000142DronesElectric vehicleUnmanned aerial vehicle routingAnt colony optimization |
| spellingShingle | Nikolaos A. Kyriakakis Themistoklis Stamadianos Magdalene Marinaki Yannis Marinakis The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries Cleaner Logistics and Supply Chain Drones Electric vehicle Unmanned aerial vehicle routing Ant colony optimization |
| title | The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries |
| title_full | The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries |
| title_fullStr | The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries |
| title_full_unstemmed | The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries |
| title_short | The electric vehicle routing problem with drones: An energy minimization approach for aerial deliveries |
| title_sort | electric vehicle routing problem with drones an energy minimization approach for aerial deliveries |
| topic | Drones Electric vehicle Unmanned aerial vehicle routing Ant colony optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2772390922000142 |
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